基于混沌理论的船舶交通事故预测

Jinyong Zhou, Lan Gao, Qing Hua
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引用次数: 1

摘要

众所周知,船舶交通事故是由多种因素引起的复杂事件,包括人、船舶、环境等因素。由于这些因素的相互作用和相互耦合,整个系统具有高度非线性的特性。由于传统线性预测的局限性,将混沌理论应用于船舶交通事故预测具有重要意义。作为一种新的尝试,本文首先分析了船舶交通事故中出现的混沌特征,然后提出了基于小波去噪的混沌自适应预测模型。理论上,该模型适用于历史记录数据量小但噪声大的船舶交通事故预测。在实际应用中,在MATLAB软件平台上的仿真结果表明了所描述模型的有效性,该模型具有较高的预测精度,能够满足实际需要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Prediction of Vessel Traffic Accident Based on Chaotic Theory
It is well known that the vessel traffic accident is a quite complex event induced by many kinds of factors, which can be concluded as persons, ships, and environment. As a result of interaction and intercoupling of these factors, the whole system has highly nonlinear characteristics. Due to the limitation of traditional linear prediction, it is significant to put the chaotic theory into the vessel traffic accident prediction. As a new attempt this paper at first analyzes chaotic characteristics appeared in vessel traffic accident, and then presents the chaotic adaptive prediction model based on wavelet de-noising. In theory this model is suitable for the vessel traffic accident prediction whose history record contains only small data sets but with much noise. In practice the following simulation results on MATLAB software platform show the effectiveness of the model described which has high prediction accuracy and can meet the actual need.
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